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Are the promises of job density taking hold in cities?

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As America’s economic and spatial divides have intensified, the dynamic between economy and place has also been evolving.

Authors

A new report from the Brookings Bass Center, Where jobs are concentrating and why it matters to cities and regions, analyzes trends in the density of jobs in 94 of the nation’s largest metro areas. The report finds that jobs in metropolitan America grew denser from 2004 to 2015, driven largely by the densification of knowledge-intensive industries, core urban counties, and “superstar cities.”

The increasing concentration of jobs in metropolitan America reveals the changing preferences of certain economic actors. Yet city and regional leaders should take note of these findings for other reasons: As the report notes, a large body of research has found that density is linked to faster economic growth, innovation, increased productivity, and improved economic mobility.

The report’s findings piqued our curiosity: Given the demographic and market trends that have been driving increased concentration of economic activity in certain areas, did we actually see that density’s economic benefits are holding up?  

To find out, we looked at how changes in metro areas’ job density are tied to their progress on economic growth, prosperity, and inclusion from 2004 to 2015, as tracked by several key indicators from the Brookings Metro Monitor.

The analysis and findings suggest that job density continues to share a strong and positive relationship to metro areas’ economic performance, but that near- and long-term improvements in workers’ share of economic growth appears to depend on other factors, too.

Increases in job density were associated with faster growth

First, we find that metro areas that saw larger increases in job density saw faster economic and job growth1 (Figure 1). On average, a metro area that saw no change in job density from 2004 to 2015 saw its gross metropolitan product (GMP) grow by 3.2%, while a metro area in which job density increased by 10 percent saw its GMP grow by nearly 4.5%–independent of other factors, such as changes in population, jobs, and industry structure. Put another way, each 1 percentage-point increase in job density was associated with an extra 0.12 percentage-point increase in GMP (Table 1).

Increases in job density were also linked to faster job growth during this period. On average, a metro area that saw no change in its job density saw its private sector jobs grow by 1.2%, while a metro area in which job density increased by 10 percent saw its jobs grow by 2.2%–independent of other factors. That works out to about a 0.1 percentage-point increase in the rate of job growth for every 1 percentage-point increase in job density after accounting for other growth factors (Table 1).

figure 1

Increases in job density were associated with increasing prosperity

Second, we find that metro areas that saw larger increases in job density also saw greater improvements in prosperity2 (Figure 2). A metro area with no change in job density saw its labor productivity—measured as GMP per job—increase 5.7%, on average, while a metro area where job density increased 10 percent saw its productivity increase nearly 6.9%. That works out to about a 0.12 percentage-point increase in the rate of productivity growth for every 1 percentage-point increase in job density after accounting for other growth factors. Changes in job density had a nearly identical marginal effect on changes in standard of living as well—measured as GMP per capita (Table 1).

figure 2

Economic size and prosperity did not diminish job density’s relationship to economic progress

Clearly, changes in job density were closely tied to metro areas’ growth and changes in prosperity during this period. But what role did a metro area’s initial economic size, prosperity, or density play in those outcomes? Not much, as it turns out.

This analysis does find more evidence of the growing divide between “superstar cities” and the rest: Larger metro areas and more prosperous metro areas, as measured by either productivity or GMP per capita, saw larger increases in job density from 2004 to 2015 (Table 2).

However, a metro area’s size and prosperity did not diminish the effects of increasing job density on improvements in economic outcomes. In fact, we find that increasing job density was associated with even larger increases in growth and productivity once we account for metro areas’ size and prosperity, suggesting that increasing job density may have a more important link to economic progress in smaller metro areas.

Meanwhile, initial levels of density appear to have had little bearing on economic growth or changes in prosperity, suggesting perhaps that increasing a metro area’s job density matters more than its initial level of density when it comes to achieving better economic outcomes.

Increases in job density bore little relationship to changes in workers’ earnings

Despite the apparent relationship between increasing job density and gains in growth and prosperity, it seems that job density had, at best, a weak relationship with changes in workers’ earnings3 during this period (Figure 3). Changes in job density had no relation to changes in average annual earnings, after accounting for other growth factors. And job density was associated with a slight decline in median annual earnings, though the evidence is mixed whether there is a relationship at all (Table 1).

3

Altogether, these findings do suggest that increasing concentrations of jobs were closely tied to faster economic growth and rising prosperity during this period. Although initial size and prosperity also contributed to these outcomes during this period, they did not affect the relevance of changes in job density.

This adds to the large body of evidence suggesting that place and density play an important role in the economic success and stability of our communities. However, high-density development alone cannot, and will not, solve the economic challenges American cities and regions are facing. When it comes to inclusive economic growth and shared prosperity, density needs to be matched with investments in people and placemaking to further drive its benefits. This includes place-based investments in workforce development and entrepreneurship to help drive job growth and productivity—and greater economic opportunity and prosperity for workers.  

 


APPENDIX

Table 1. Results of regression analyses for economic indicators (2004-2015)

Dependent variable:

Change in

GMP

Change in

private jobs

Change in productivity

Change in standard of living

Change in earnings per worker

Change in median wage (06-15)

Change in job density

0.13*

0.10*

0.12*

0.12*

0.02

-0.02

Controls

Changes in population, jobs, and industry structure

Constant

3.2

1.2

5.7

3.4

6.2

-0.5

R-squared

0.688

0.780

0.347

0.470

0.257

0.390

N = 94, * p < 0.05

 

Table 2. Results of regression analyses for changes in job density

Dependent variable:

Change in job density (2004-2015)

Independent variable

Log of GMP, 2004

Productivity, 2004

Standard of living, 2004

Coefficient

9.83*

0.0004*

0.001*

Constant

-240

-36

-32

R-squared

0.162

0.093

0.121

N = 94, * p < 0.05

Footnotes

  1. The Metro Monitor measures growth in gross metropolitan product (GMP), number of jobs, and number of jobs at young firms. Here we only use GMP and number of private jobs for our analysis. Change in GMP is measured in inflation-adjusted terms. Data on GMP are from the Bureau of Economic Analysis (BEA) of the U.S. Department of Commerce, data on private jobs are from the U.S. Census Bureau’s LEHD Origin-Destination Employment Statistics program. GMP estimates are based on the U.S. Office of Management and Budget’s August 2017 CBSA definitions. All other indicators are based on OMB’s September 2018 CBSA definitions.
  2. Like in the Metro Monitor, we measure prosperity by productivity (GMP per job) and the standard of living (GMP per capita). Data on GMP are from the BEA, data on jobs are from Emsi, and data on population are from the Census Population Estimates program. All these estimates are based on the 2017 CBSA definitions.
  3. Change in the median wage and the average annual wage per job are measured in inflation-adjusted terms. Data on the median wage are from the Census Public-Use Microdata Series (PUMS) and data on the average earnings are from the Emsi estimates. Both measures are based on the 2018 CBSA definitions.
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